【正文】 行一階微分或二階微分運(yùn)算，求得梯度最大值或二階導(dǎo)數(shù)的過零點(diǎn)，最后選取適當(dāng)?shù)拈]值提取邊界。本文對(duì)邊緣檢測(cè)理論和算法作了深入的研究，在具體分析各類傳統(tǒng)的邊緣檢測(cè)算法的基礎(chǔ)上，重點(diǎn)研究了 Canny算法，并結(jié)合改進(jìn)的 MTM算法及 Otsu算法對(duì) Canny算法中的濾波方法和雙門限選取方法進(jìn)行改進(jìn)。關(guān)鍵詞：圖像處理； 邊緣檢測(cè)； Canny 算子； 濾波； 自適應(yīng)閾值東華理工大學(xué)長(zhǎng)江學(xué)院畢業(yè)設(shè)計(jì)（論文） 摘要ABSTRACTDigital image edge detection plays an import part in image analysis, such as image segmentation, interested region recognition and region shape it’s an import method in image feature extraction of image edge includes the valuable infotmation of the image which can be use in image understanding and through edge detection,we can greatly reduce the calculation of image analysis and processing in the following ,the first step of image understanding and analysis is edge detection,and it has been the most active topic in the machine vision research field,also it plays an import part in engineering application.Most of the traditional edge detection algorithms,such as Roberts,Sobel,Prewitt, Kirsch,Laplacian ,just construct an edge detection algorithm with a small neighborhood in each pixel of the original image,and then carry out with first differential or second differential operator in order to obtain the maximum gradient or the zerocrossing point of the second derivative,finally select an appropriate threshold to extract the these algorithms share the same shortings,for example,they are sensitive to noise,they can’t select threshold adaptively,and the detection results are not so well.In this paper,we do a deep research on the edge detection theory and algorithm, base on analyzing the traditional edge detection algorithm in detail,we focus on Canny algorithm,bined with MTM algorithm and Otsu algorithm to improve the filtering method and dual threshold selection method in Canny algorithm,and we call the imprived algorithm CMO for ,we use MATLAB to implement CMO algorithm,and the experiment results show that CMO algorithm can get better results than traditional Canny algorithm.Key words: Image Processing。 Canny。 Adaptive Threshold東華理工大學(xué)長(zhǎng)江學(xué)院畢業(yè)設(shè)計(jì)（論文） 目錄目 錄緒論 ................................................................................................................................11. 數(shù)字圖像處理 ...........................................................................................................2 數(shù)字圖像處理的發(fā)展 ..........................................................................................2 數(shù)字圖像處理的應(yīng)用 ..........................................................................................2 數(shù)字圖像邊緣定義及邊緣提取方法概述 ..........................................................4 目前邊緣檢測(cè)存在的問題 ..................................................................................6 本文主要研究工作 ..............................................................................................62. 圖像濾波 ...................................................................................................................7 圖像噪聲的定義 ..................................................................................................7 圖像噪聲的來源 ..................................................................................................7 圖像噪聲的濾除 ..................................................................................................8 領(lǐng)域平均法 .............................................................................................................................8 加權(quán)平均法 ...........................................................................................................................10 中值濾波 ...............................................................................................................................11 空域低通濾波 .......................................................................................................................123. 傳統(tǒng)邊緣檢測(cè)算法的研究與分析 .........................................................................14 圖像邊緣檢測(cè)方法分類 ....................................................................................14 基于空間域上微分算子的邊緣提取方法 ...........................................................................14 基于圖像濾波的邊緣提取方法 ...........................................................................................15 圖像邊緣評(píng)價(jià)指標(biāo) ............................................................................................16 尺度對(duì)性能指標(biāo)的影響 ....................................................................................17 經(jīng)典邊緣檢測(cè)方法綜述 ....................................................................................18 基于灰度直方圖的邊緣檢測(cè) ...............................................................................................18 ROBERTS 算子 ..................................................................................................19 Sobel 算子 ..............................................................................................................................20 Prewitt 算子 ...........................................................................................................................21 其他邊緣檢測(cè)方法 ...............................................................................................................224. CANNY 算子、MTM 算法和 OTSU 算法研究及改進(jìn) ......................................26 CANNY 邊緣檢測(cè)準(zhǔn)則 ........................................................................................26 MTM 算法 ..........................................................................................................30 OTSU 算法 ...........................................................................................................32 試驗(yàn)過程及結(jié)果分析 ........................................................................................34結(jié)論 ..............................................................................................................................38致 謝 .........................................................................................